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affect early cellular gene expression
Bo Yang, Xuefeng Qi, Zhijie Chen, Shuying Chen, Qinghong Xue, Peilong Jia,
Ting Wang, Jingyu Wang
To cite this version:
RESEARCH ARTICLE
Binding and entry of peste des petits
ruminants virus into caprine endometrial
epithelial cells profoundly affect early cellular
gene expression
Bo Yang
1†, Xuefeng Qi
1†, Zhijie Chen
1, Shuying Chen
1, Qinghong Xue
2, Peilong Jia
1, Ting Wang
1and Jingyu Wang
1*Abstract
Peste des petits ruminants virus (PPRV), the etiological agent of peste des petits ruminants (PPR), causes an acute or subacute disease in small ruminants. Although abortion is observed in an unusually large proportion of pregnant goats during outbreaks of PPR, the pathogenic mechanism underlying remains unclear. Here, the gene expres-sion profile of caprine endometrial epithelial cells (EECs) infected with PPRV Nigeria 75/1 was determined by DNA microarray to investigate the cellular response immediately after viral entry. The microarray analysis revealed that a total of 146 genes were significantly dysregulated by PPRV internalization within 1 h post-infection (hpi). Of these, 85 genes were upregulated and 61 genes were downregulated. Most of these genes, including NFKB1A, JUNB, and IL1A, have not previously been reported in association with PPRV infection in goats. Following viral replication (24 hpi), the expression of 307 genes were significantly upregulated and that of 261 genes were downregulated. The data for the genes differentially expressed in EECs were subjected to a time sequence profile analysis, gene network analysis and pathway analysis. The gene network analysis showed that 13 genes (EIF2AK3, IL10, TLR4, ZO3, NFKBIB, RAC1, HSP90AA1, SMAD7, ARG2, JUNB, ZFP36, APP, and IL1A) were located in the core of the network. We clearly demonstrate that PPRV infection upregulates the expression of nectin-4 after 1 hpi, which peaked at 24 hpi in EECs. In conclusion, this study demonstrates the early cellular gene expression in the caprine endometrial epithelial cells after the binding and entry of PPRV.
© The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Introduction
Peste des petits ruminants virus (PPRV) is a Morbillivirus of the family Paramyxoviridae, which causes an acute, highly contagious, and fatal disease that primarily affects goats and sheep. In general, goats are more severely affected than sheep [1–3]. It is noteworthy that PPRV infection often causes fetal mummification, abortions late in pregnancy, or the birth of dead or weak lambs that die within a couple of days [4, 5]. Although a number of
studies for PPRV infection in vitro based on Vero cells, which are currently considered highly permissive cells for the isolation and propagation of various viruses [6–8], little is known about the characteristics of the PPRV-infected reproductive system in goats.
Like all morbilliviruses, PPRV has a well-established lymphatic and epithelial tissue tropism [9, 10]. Similar to Measles virus (MV), PPRV has three cellular recep-tors: CD46, the protein signaling lymphocyte activation molecule (SLAM or CD150), and the poliovirus receptor-like protein 4 (also known as PVRL4 or nectin-4). Ovine nectin-4 was identified as the epithelial receptor for PPRV. It is predominantly expressed in epithelial tissues and is encoded by multiple haplotypes in sheep breeds around the world [11]. Cell lines expressing nectin-4 have
Open Access
*Correspondence: nwsuaf4409@126.com
†Bo Yang and Xuefeng Qi contributed equally to this work 1 College of Veterinary Medicine, Northwest A&F University,
Yangling 712100, Shaanxi, China
previously been used to propagate MV, Canine distemper
virus (CDV), and PPRV [11–16].
Although the pathogenesis of PPRV infection has been relatively well described in experimental animals, only a few studies have shed light on the molecular events fol-lowing PPRV infection in goats [17, 18]. Therefore, it is important to determine the responses of individual caprine cell types to PPRV infection. The epithelial cells that are in contact with the virus may be responsible for generating the immune response required for the initia-tion of inflammainitia-tion. Lingual and buccal mucosae and lung epithelial tissue infected by PPRV show signifi-cant inducible nitric oxide synthase (iNOS), interferon γ (IFN-γ), and tumor necrosis factor α (TNF-α) expres-sion, which may play important roles in the initiation and regulation of the cytokine responses [18]. There has been little close study of the progression or causes of the PPRV-associated pathology, except for a recent thorough histological investigation of the distribution of the virus during the early stages of infection [19], which showed that the virus spreads in a similar way to MV in humans [20, 21]. Interestingly, apoptosis was also observed in UV-inactivated MV-treated peripheral blood mononu-clear cells (PBMCs), suggesting that MV replication is not necessary for virus-induced gene expression in the host cells [22].
The aim of this study was to determine the gene expres-sion profile of caprine endometrial epithelial cells (EECs) in response to the PPRV vaccine virus, using the DNA microarray technology, and to thus clarify the virus–host interactions. We first determined the gene expression profile of EECs 1 h after in vitro exposure to PPRV and compared it with that of mock-exposed cells. We also distinguished between the responses induced by virion binding or entry and the responses that require viral gene expression.
Materials and methods
Cells and viruses
The caprine EECs were kindly provided by Prof. Yap-ing Jin (Northwest A&F University YanglYap-ing, Shaanxi, China), and we confirmed that their secretory function was consistent with that of primary endometrial epithe-lial cells [23, 24]. The cells were immortalized by trans-fection with human telomerase reverse transcriptase (hTERT), as previously reported [25], and cultured in Dulbecco’s minimal essential medium/nutrient mixture F-12 Ham’s medium (DMEM/F12) supplemented with 10% fetal bovine serum (FBS), penicillin (100 IU/mL), and streptomycin (10 μg/mL) at 37 °C under 5% CO2.
The PPRV vaccine strain, Nigeria 75/1, was obtained from the Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences (Lanzhou, China). The
viral stock was prepared by collecting the infected cell supernatant when a cytopathic effect (CPE) was appar-ent in about 80% of the cells. The cells were freeze– thawed three times and stored as aliquots at −80 °C. The viral titers were estimated with the method of Reed and Muench, and expressed as 50% tissue culture infective doses (TCID50)/mL.
Kinetics of viral internalization
EECs grown in 12-well plates (3 × 105 cells/well) were
infected with PPRV at a multiplicity of infection (MOI) of 2, and incubated at 37 °C. To separate the adsorption and internalization processes, the EECs were pretreated with PPRV at 4 °C for 1 h and then shifted to 37 °C. Pro-teinase K treatment significantly affected the number of virions attached to the cell surface, suggesting that pro-teinase K removes the viruses attached to cells [26]. At different time points, the cells were washed with phos-phate-buffered saline (PBS) and treated with proteinase K (2 mg/mL) (Solarbio, China) for 45 min at 4 °C to remove the adsorbed but not internalized virus. The proteinase K was then inactivated with 2 mM phenylmethylsulfonyl fluoride in PBS with 5% bovine serum albumin (BSA), and the cells were washed with PBS–0.5% BSA with low-speed centrifugation. Finally, the cell pellet was resus-pended in DMEM/F12 and serial tenfold dilutions of the cell suspension were plated. EEC monolayers were grown in 96-well plates containing DMEM with 2% FBS. Eight replicates were established for each dilution, and 100 μL of virus diluent was added to each well. The cells were incubated at 37 °C under 5% CO2 for about 5–7 days, and
the numbers of wells with or without CPE were counted. TCID50 was calculated with the Reed–Muench method
and used to calculate the infectivity of the viral stocks: infectivity (plaque-forming units/mL) = 0.69 × TCID50.
Each test was performed in triplicate. To determine the rate of virus internalization, a parallel set of cultures was processed under the same conditions, except that pro-teinase K was replaced with PBS.
Western blotting analysis
membranes (Millipore, Billerica, MA, USA). The mem-branes were blocked with 5% nonfat milk and incubated with primary antibodies, and then with horseradish-per-oxidase-conjugated secondary antibodies (Santa Cruz Biotechnology, CA, USA). The following antibodies were used: anti-PPRV-N monoclonal antibody provided by the China Animal Health and Epidemiology Center (Qing-dao, China), anti-nectin-4 (Abcam, Cambridge, MA, USA), and anti-β-actin (Santa Cruz Biotechnology, CA, USA). The bound antibodies were detected with western chemiluminescent HRP substrate (Millipore, MA, USA). The data are expressed as the means ± standard devia-tions (SD) of three independent experiments.
Sample selection and DNA microarray
PPRV was adsorbed onto the cells at an MOI of 2 at 4 °C for 1 h. After full adsorption, the cells were incubated at 37 °C for 1 h (PPRV 1 hpi, N = 3) or 24 h (PPRV 24 hpi,
N = 2). To determine the rate of viral internalization, a
parallel set of cultures was processed under the same conditions, except that PPRV was replaced with culture medium (control, N = 3). RNAiso Plus (1 mL; Takara, Tokyo, Japan) was added to each group of samples. The RNA quantity and quality were measured tometrically with a NanoDrop ND-1000 spectropho-tometer (Thermo Fisher Scientific, Waltham, MA, USA; Additional file 1). The integrity of the RNA was assessed with standard denaturing agarose gel electrophoresis.
Because no genomic reference sequence for Capra
hircus is available, the Sheep Gene Expression
Microar-ray, 8 × 15 K was used (Agilent Technologies, CA, USA), which contains >15 000 sheep genes and transcripts, all with public domain annotations.
RNA labeling and array hybridization
Sample labeling and array hybridization were performed according to the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technolo-gies). Briefly, the total RNA from each sample was lin-early amplified and labeled with Cy3-UTP. The labeled complementary RNAs (cRNAs) were purified with the RNeasy Mini Kit (Qiagen, Düsseldorf, Germany), and the concentrations and specific activities of the labeled cRNAs (pmol Cy3/μg cRNA) were measured with a Nan-oDrop ND-1000 spectrophotometer. Each labeled cRNA (1 μg) was fragmented by the addition of 11 μL of 10 × Blocking Agent and 2.2 μL of 25 × Fragmentation Buffer, with heating at 60 °C for 30 min. Then 55 μL of 2 × GE Hybridization Buffer was added to dilute the labeled cRNAs. Hybridization solution (100 μL) was dispensed into the gasket slide of the array, which was then attached to the gene expression microarray slide. The slides were incubated for 17 h at 65 °C in an Agilent Hybridization
Oven. The hybridized arrays were washed, fixed, and scanned with an Agilent DNA Microarray Scanner (Part Number G2505C).
The Agilent Feature Extraction software (version 11.0.1.1) was used to extract the array images. Quan-tile normalization and subsequent data processing were performed with the GeneSpring GX v11.5.1 software package (Agilent Technologies). After quantile normali-zation of the raw data, the genes that that were flagged in Detected (“All Targets Value”) in at least two of eight samples were selected for further analysis. Genes that were statistically significantly differentially expressed in the two groups were identified with Volcano Plot filter-ing. The hclust function (R package stats) was used to perform hierarchical clustering (Ward’s method) [27]. Heatmaps were produced with the heatmap.2 function (R package gplots) [28].
The datasets for the microarray analysis of the whole transcriptome, based on eight samples, were deposited in the Gene Expression Omnibus (GEO) database under accession number GSE85204.
Analyses of differentially expressed genes (DEGs)
Time sequence profile analysis of gene expression
We selected a set of distinct and representative temporal expression profiles. These model profiles corresponded to the possible profiles of the changes in the expression of the genes over time. Each gene was assigned to the model profile that most closely matched its expression profile, which was determined with a correlation coefficient. Because the model profiles were selected independently of the data, an algorithm could determine which profiles had a statistically significantly higher number of genes assigned to them using a permutation test. It then used standard hypothesis testing to determine which model profiles had significantly more genes assigned under the true ordering of time points compared with the average number assigned to the model profile in the permutation runs. The significant model profiles could then be either analyzed further independently, or grouped together based on their similarity to form clusters of significant profiles.
Construction of the gene coexpression network
profiles (profiles 2, 7, 8, and 13) to construct a coexpres-sion network. The network edges were specified to fea-ture correlation coefficients of >0.9 to ensure strong gene coexpression relationships. The genes labeled with differ-ent colors represdiffer-ent differdiffer-ent degrees of connectedness. The network of genes was analyzed with the SPSS soft-ware and visualized with the Cytoscape 2.8.3 softsoft-ware [30].
Pathway analysis
We performed a pathway analysis of the DEGs based on the latest Kyoto Encyclopedia of Genes and Genomes (KEGG) Database [31]. The P values denote the signifi-cance of the pathways (cutoff is 0.05).
Validation with qRT–PCR
To validate the microarray data, the expression of the genes upregulated at 1 hpi (vs. the control), such as TNF,
NFKB1A, JUNB, IL1A, TGFB3, and CXCL1, were
deter-mined with the qRT–PCR analysis of three independent biological replicates. When we compared their expres-sion at 24 and 1 hpi, the TLR4 gene was upregulated and genes TNF, JUNB, NFKB1A, NFKB1B, IL1A, HSP90AA1, and SMAD7 were downregulated. The primer sequences used are listed in Table 1. To validate the assay, the purified products were sequenced to confirm that the
correct target was amplified. We calculated the relative expression level of each gene with the formula 2−△△CT
[32], where CT is the threshold cycle, normalized to the goat housekeeping gene glyceraldehyde-3-phosphate-dehydrogenase (GAPDH), and represented it as the fold change relative to the mean of the samples. The standard deviations were calculated using the relative expression ratios of three replicates for each gene analyzed.
Statistical analysis
All data obtained in this study were analyzed with an independent-samples t test and expressed as the means ± standard deviations (SD) of at least three inde-pendent samples. P values of less than 0.05 were consid-ered significant, and P < 0.01 was considconsid-ered extremely significant.
Results
Kinetics and rate of PPRV internalization
To accurately define the conditions of the viral inter-nalization assay required to monitor PPRV entry during different treatments, we first determined the kinetics and rate of virus penetration into the EECs by measur-ing the productive internalized viral particles. As shown in Figure 1, significant PPRV particles were detached from the cells by proteinase K at 30 min postinoculation
Table 1 Primers for selected genes analyzed with qRT–PCR
Gene symbol Primer sequence (5ʹ–3ʹ) GenBank accession Product (bp)
compared with the control cells (P < 0.01). After incuba-tion for 60 min, most of viruses were resistant to protein-ase K treatment compared with the control treatment, indicating the successful internalization of the infectious virions. Therefore, in the subsequent DNA microarray
experiments, 1 h after PPRV infection was considered the optimal time point to measure viral entry.
Receptor nectin‑4 expression in EECs inoculated with PPRV
To accurately define the conditions of the viral replication cycle in the host cells, PPRV strain Nigeria 75/1 was used to infect EECs. As shown in Figure 2A, experimental infection of the EECs with PPRV resulted in large syncytia, which formed at 72–120 hpi. The refractivity of the infected cells was also significantly enhanced. In contrast, no syncytia or visible CPE were observed within 24 hpi. Similar expres-sion of nectin-4 and PPRV-N in the EECs exposed to the Nigeria 75/1 strain was detected with a western blotting assay. The viral protein was detected as early as 12 hpi and its levels increased until 48 hpi, followed by a slight decline (Figures 2B and C). The overall changes in the receptor nectin-4 levels expressed in the PPRV-infected cells were consistent with the changes in the PPRV-N expression detected, except that the receptor protein was first detected at 3 hpi and peaked at 24 hpi in the EECs (Figures 2B and C). Therefore, in the subsequent DNA microarray experi-ments, 24 h after PPRV infection was considered the opti-mal time point to determine early viral replication and the highest expression of the receptor before CPE occurred.
DNA microarray data analysis
We used the Agilent one-color Sheep Gene Expression Microarray, 8 × 15 K (Catalogue No. 019921) to monitor
Figure 1 Kinetics and rate of PPRV internalization into caprine endometrial epithelial cells (EECs). EECs were infected with PPRV
for 1 h at 4 °C and then transferred to 37 °C. At the indicated time points after infection, the extracellular virus was inactivated with proteinase K. Results are shown as the TCID50 of the internalized virus
compared with the control, in which PBS was substituted for protein-ase K, and are presented as the means ± standard deviations (SD) of three independent experiments. *P < 0.05, **P < 0.01.
Figure 2 PPRV replication and nectin-4 expression in EECs. A Morphological changes in infected EECs at the indicated time points
(magnifi-cation, ×100). B PPRV-infected cells were collected for western blotting with anti-PPRV-N and anti-nectin-4 antibodies at the indicated time points. β-Actin was detected as the loading control. Representative results are shown and similar results were obtained in three independent experiments.
C Analysis of the relative levels of nectin-4 and PPRV-N in infected EECs. The optical densities for the nectin-4, PPRV-N, and β-actin protein bands
the cellular gene expression after viral adsorption and internalization by the cells. A minimum fold-change cut-off value of 2.0 was set to filter the data. A cluster analy-sis showed distinct trends in the expression of genomic
transcripts in the cells at 1 and 24 h after in vitro expo-sure to PPRV compared with that in the mock-exposed control cells (Figure 3A). Of the >15 000 genes analyzed, 146 were significantly more strongly expressed in the
Figure 3 Heatmaps of differentially expressed genes. A Unsupervised hierarchical clustering based on the set of all differentially expressed
PPRV-infected EECs at 1 hpi than in the mock-infected cells (P < 0.05). Of these genes, 85 were upregulated and 61 were downregulated (Additional file 2). A proportion of the DEGs, which were associated with viral infection or inflammatory cytokines, such as IRF1, JUNB, TNF,
CXCL1, IL1, and TGFB3, were shown in a heatmap
(Fig-ure 3B), and the 25 most strongly DEGs (Fold change > 2, P < 0.01) are shown in Table 2. We also compared the expression of DEGs at 1 and 24 hpi. The expression of 307 genes were significantly upregulated and that of 261 genes were downregulated in the cells at 24 hpi relative to their expression at 1 hpi (Additional file 3). A propor-tion of the DEGs, which were associated with antiviral processes and immunity, such as TLR4, HSP90AA1, FOS, and RAC1, were shown in a heatmap (Figure 3C), and the 30 most strongly DEGs (Fold change > 3, P < 0.01) are listed in Table 3. Moreover, we compared the expres-sion of DEGs at 24 hpi and mock-infected cells. The expression of 319 genes were significantly upregulated and that of 276 genes were downregulated in the PPRV-infected EECs at 24 hpi than in the mock-PPRV-infected cells
(Additional file 4), which has a great consistency with the data of comparision between 24 and 1 hpi. A proportion of the DEGs, which were associated with antiviral pro-cesses and immunity, such as CASP3, SMAD7, IL10 and
DDX3X, were shown in a heatmap (Figure 3D), and the 30 most strongly DEGs (Fold change > 3, P < 0.01) are listed in Table 4.
Model profile and gene coexpression analysis
We detected 146 DEGs at PPRV 1 hpi (vs. the control) and 568 DEGs at PPRV 24 hpi (vs. the 1 hpi), but 110 common genes were differentially expressed at both time points, so the total number of DEGs was 604. To further examine the most significant target genes among these 604 DEGs, we used 16 model profiles to summarize the expression patterns of the genes. As shown in Figure 4, among the 16 patterns, we identified six patterns of genes that showed significant P values of < 0.05 (colored boxes). Among these patterns, the four most significant pat-terns were profiles Nos 2, 7, 8, and 13. Whereas profiles No. 8 and No. 13 contained 318 genes whose expression
Table 2 Top 25 DEGs in EECs at 1 hpi compared with mock-infected cells Gene symbol Genbank acces‑
sion Regulation P‑value Fold change Description
NFKBIA NM_001166184 Up 8.81E−06 8.2231 Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha
IRF1 NM_001009751 Up 2.30E−06 5.051156 Interferon regulatory factor 1 OMYHC2A EE775159 Up 0.002788255 4.7159348 Myosin heavy chain 2a TAC1 NM_001082596 Down 0.00153884 4.2892804 Tachykinin, precursor 1
ICAM-1 NM_001009731 Up 0.002129168 3.683435 Intercellular adhesion molecule-1 precursor IL1A NM_001009808 Up 2.02E−04 3.55534 Interleukin 1, alpha
EDN1 NM_001009810 Down 1.66E−04 3.4484744 Endothelin 1
ZFP36 NM_001009765 Up 5.78E−04 3.4401255 Zinc finger protein 36, C3H type, homolog (mouse) CHI3L1 AY392761 Up 7.28E−05 3.1458294 Signal processing protein chitinase 3-like 1
SERPINC1 NM_001009393 Down 1.89E−04 3.089472 Serpin peptidase inhibitor, clade C (antithrombin), member 1 IL-1B NM_001009465 Up 3.37E−04 2.9417644 Interleukin 1 beta
LOC100037673 DY511533 Down 0.001184922 2.8017275 Adult sheep fracture callus 10d Ovis aries Cdna TGFB3 AY656798 Up 4.33E−05 2.5155127 Transforming growth factor beta 3
JUNB GT876239 Up 4.88E−05 2.4711938 Jun B proto-oncogene
APP XM_004002800 Down 0.002011435 2.4293847 Amyloid beta (A4) precursor protein, transcript variant 2 LOC101115904 XM_004016735 Up 0.002455467 2.36435 Uncharacterized protein LOC101115904
TRIP4 DQ399300 Up 3.36E−04 2.3092742 Hyroid hormone receptor interactor 4 ARG2 DQ152925 Up 5.19E−04 2.288348 Arginase type II
CLDN7 FE026534 Up 0.002388065 2.2819793 Claudin 7
TNF NM_001024860 Up 0.002930126 2.267481 Tumor necrosis factor FBXO33 XM_004018121 Down 0.001120999 2.2263784 F-box protein 33 MCP-3 Y13462 Up 2.35E−04 2.1799133 Mast cell proteinase-3 SDC4 XM_004014854 Up 0.001711099 2.1769335 Syndecan 4
increased slightly before 1 hpi but markedly after PPRV infection, profiles No. 2 and No. 7 contained 222 down-regulated genes whose expression decreased markedly after 1 hpi (Figure 5).
The genes in profiles Nos 2, 7, 8, and 13 were then ana-lyzed and identified with a gene coexpression network to determine which gene or genes play/s a pivotal role in the early stage of PPRV infection. The gene network was con-structed from functional gene associations. In a network, the cycle nodes represent genes and the edges between two nodes represent the interactions between the genes, which are quantified by their degree of interaction. The size and color of the cycle node represent the degree of interaction within the network, which describes the
number of single genes that are regulated by the gene. The higher the degree, the more central the gene is within the network. This analysis produced the set of interactions illustrated in Figure 6. The genes with high-est degree (degree ≥ 10) in our results were considered to have core status within the large-scale gene network made up of 13 DEGs. Most of these genes were involved in translation initiation, protein synthesis, transcellular transport, cellular stress adaptation, immunoregulation, or inflammation. In this network, genes encoding trans-membrane proteins, such as toll-like receptor 4 (TLR4), were highly connected, interacting with MYF5, INSL3,
TAC1, etc. Interleukin 10 (IL-10) is a cytokine with
multiple, pleiotropic effects in immunoregulation and
Table 3 Top 30 DEGs in EECs at 24 hpi compared with 1 hpi Gene symbol Genbank acces‑
sion Regulation P‑value Fold change Description
EGR1 NM_001142506 Down 0.002950523 19.151798 Early growth response 1
FOS NM_001166182 Down 0.00342968 11.567851 FBJ murine osteosarcoma viral oncogene homolog BHLHE40 NM_001129741 Down 1.08E−04 9.15262 Basic helix-loop-helix family, member e40 ZFP36 NM_001009765 Down 4.51E−04 8.795816 Zinc finger protein 36, C3H type, homolog (mouse) IL1A NM_001009808 Down 3.00E−04 7.487845 Interleukin 1, alpha
TRIB1 XM_004011943 Down 1.57E−04 7.3840594 Tribbles homolog 1 (Drosophila) SEPP1 XM_004017013 Up 0.002879895 7.0929484 Selenoprotein P, plasma 1 JUNB GT876239 Down 2.85E−04 6.882143 Jun B proto-oncogene EDN1 NM_001009810 Up 3.54E−05 5.993922 Endothelin 1
MID1IP1 XM_004022004 Down 1.82E−04 5.810994 MID1 interacting protein 1 PLAU NM_001163593 Down 0.001708808 5.75504 Plasminogen activator, urokinase BTG2 NM_001246210 Down 3.04E−04 5.2239857 BTG family, member 2
ARG2 DQ152925 Down 7.10E−06 5.166251 Arginase type II
BMP7 DQ192015 Up 1.67E−04 4.7991242 Bone morphogenic protein 7
NFKBIA NM_001166184 Down 4.69E−05 4.5390587 Ovis aries nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha
ZO3 AJ313186 Up 7.84E−04 4.2812595 Tight junction protein 3 KIAA0101 XM_004010534 Up 4.33E−04 4.1474485 KIAA0101 ortholog
LOC101115904 XM_004016735 Down 0.003668104 3.9130077 Uncharacterized LOC101115904 ARL4C EE764200 Down 0.001940122 3.7775939 ADP-ribosylation factor-like 4C
APP XM_004002800 Up 0.001847968 3.7057652 Amyloid beta (A4) precursor protein, transcript variant 2 SMAD7 EE805013 Down 7.16E−04 3.6945896 SMAD family member 7
IL10 NM_001009327 Up 0.002752419 3.683875 Interleukin 10
MS4A2 AJ318333 Up 1.18E−05 3.6728828 Membrane-spanning 4-domains, subfamily A, member 2 (high affinity IgE receptor beta subunit)
HSPA5 XM_004005637 Down 6.33E−04 3.6717205 Heat shock 70 kDa protein 5 (glucose-regulated protein, 78 kDa) ALDH1A1 NM_001009778 Up 9.93E−05 3.6705909 Aldehyde dehydrogenase 1 family, member A1
VDUP1 EE783894 Up 0.00445289 3.6468685 Vitamin D3 upregulated protein 1 MT3 NM_001009755 Down 7.00E−04 3.6455984 Metallothionein 3
ADAMTS1 GU437212 Up 0.001361214 3.609648 ADAM metallopeptidase with thrombospondin type 1 motif 1 NFKBIZ XM_004002892 Down 7.30E−04 3.4408464 Nuclear factor of kappa light polypeptide gene enhancer in B-cells
inhibitor, zeta, transcript variant 1
inflammation, and its gene was found to be connected to
ZO3, EIF2AK3, UCP2, TRYPTASE-1, etc. HSP90AA1 was
connected to RAC1, SMAD7, PLAU, NFKBIB, etc. APP, which encodes a precursor of the β-amyloid protein, known for its proinflammatory activity, was downregu-lated and connected to IL1A, AGR2, ZFP36, JUNB, etc.
Pathway overrepresentation analysis of gene expression
To systematically identify the biological associations of the DEGs and the pathways associated with PPRV infection, we performed a pathway overrepresenta-tion analysis (ORA) with the KEGG Database. At 1 hpi, this analysis identified 38 KEGG pathways closely asso-ciated with the upregulated gene functions that were statistically enriched relative to their expression in mock-infected cells (P < 0.05). The top 10 pathways of upreg-ulated genes were directly related to proinflammatory signaling pathways (Table 5). Many of the genes identified
as central nodes in the gene coexpression analysis (IL1A,
JUNB, NFKBIA, etc.) also occupied central positions
in the signaling pathways identified. No pathway was enriched with any gene downregulated at 1 hpi. We also compared the datasets established for the PPRV-infected cells at 24 and 1 h. Twenty-three pathways were closely related to the upregulated genes and the top 10 differen-tially regulated pathways are shown in Table 5. In con-trast, the differentially upregulated signaling responses among the top 10 pathways at 24 hpi were strongly asso-ciated with the anti-inflammatory, cell-cycle, and steroid hormone regulation signaling pathways. Many genes that occupy central positions in these signaling pathways also were identified at central nodes in the gene coexpression analysis (IL10 and TLR4). Interestingly, downregulated genes were associated with 64 pathways at 24 hpi. The top 10 pathways associated with immune regulation were identified (Table 5). In addition, when we compared the
Table 4 Top 30 DEGs in EECs at 24 hpi compared with mock-infected cells
Gene symbol Genbank accession Regulation P‑value Fold change Description
EGR1 NM_001142506 Down 0.002213208 18.65667 Early growth response 1
FOS NM_001166182 Down 1.36E−04 12.473125 FBJ murine osteosarcoma viral oncogene homolog TRIB1 XM_004011943 Down 1.44E−04 8.222353 Tribbles homolog 1
TAC1 NM_001082596 Down 0.001494624 7.357662 Tachykinin, precursor 1 IL10 NM_001009327 Up 0.001118106 7.0200763 Interleukin 10
BMP7 DQ192015 Up 0.00262231 6.539379 Bone morphogenic protein 7 VDUP1 EE783894 Up 3.87E−04 5.696548 Vitamin D3 upregulated protein 1 ISL1 AY949772 Up 3.02E−04 5.673369 Insulin gene enhancer binding protein 1 ZO3 AJ313186 Up 3.90E−04 5.6202655 Tight junction protein 3
CSN3 NM_001009378 Up 0.002891978 5.392171 Casein kappa
BHLHE40 NM_001129741 Down 6.93E−04 5.160135 Basic helix-loop-helix family, member e40 EP4b AF400121 Up 0.003765256 5.08562 E-type prostanoid receptor 4, member b SGP-1 S82555 Up 0.006463662 5.047211 Sulfated glycoprotein-1
MYF5 AF434668 Up 0.001443176 4.4979677 Myogenic factor-5 TRYPTASE-1 NM_001009412 Up 0.005506944 4.4218497 Tryptase
FSHB NM_001009798 Up 0.004583429 4.1606646 Follicle stimulating hormone, beta polypeptide LOC443181 AF532967 Up 0.001282363 4.126875 Orexin receptor 2
ZFP36 NM_001009765 Down 0.007023024 4.094527 Zinc finger protein 36
SAMSN1 XM_004002825 Up 2.78E−04 4.0811343 SAM domain, SH3 domain and nuclear localization signals 1 MID1IP1 XM_004022004 Down 4.84E−05 4.05381 MID1 interacting protein 1
CD28 NM_001009441 Up 7.68E−04 3.9630585 Cluster of Differentiation 28 TSHB X90775 Up 0.001051094 3.8141446 Beta-thyrotropin
ARL4C EE764200 Down 7.23E−04 3.800169 ADP-ribosylation factor-like 4C
RABL6 XM_004007077 Up 0.001573537 3.7721963 RAB, member RAS oncogene family-like 6 UCP2 NM_001280682 Up 0.001399294 3.7484381 Uncoupling protein 2
MS4A2 AJ318333 Up 3.66E−05 3.5462005 High affinity IgE receptor beta subunit RC3H2 XM_004005656 Down 0.001738322 3.5258648 Ring finger and CCCH-type domains 2 CYP1A1 NM_001129905 Down 4.90E−04 3.5247505 Cytochrome P4501A1
datasets established for PPRV-infected cells at 24 h and mock-infected cells, the differentially signaling pathways are consistent with the data of comparision between 24 and 1 hpi as shown in Table 5. When we compared the differentially regulated pathway (ORA) datasets in 1 h PPRV-infected cells and mock-infected cells, and in PPRV-infected cells at 24 and 1 h, the regulatory path-ways identified showed opposite trends (Figure 7). Whereas PPRV insult caused the upregulation of genes largely related to the TNF, TLR, T cell receptor, RIG1, chemokine, and NF-κB signaling pathways (Figure 7A), most these genes were significantly downregulated in the cells at 24 hpi relative to their expression at 1 hpi (Figure 7B).
qRT–PCR verification of the microarray data
To verify the DNA microarray data, qRT–PCR was used to analyze the same RNA samples as were used in the original microarray experiment for 10 selected genes. At 1 hpi, the trends in expression of the genes ana-lyzed with qRT–PCR, including TNF, NFKB1A, CXCL1,
JUNB, IL1A, and TGFB3, were consistent with the trends
observed with the DNA microarray analysis (Figure 8A). However, the increase in the expression of TLR4 at 24 hpi was significantly greater when detected with PCR than when detected with the microarray analysis (Figure 8A). The expression levels of genes TNF, JUNB, NFKB1A,
NFKB1B, IL1A, HSP90AA1, and SMAD7 did not differ
markedly between the microarray data and the qRT–PCR data (Figure 8B).
Discussion
Several strains of MV and PPRV infect epithelial cells using nectin-4 as the receptor [33]. Previous stud-ies have shown that wild-type MV infection upregu-lates nectin-4 expression in human and murine brain endothelial cells [13]. The present study confirms the same trends in the changes in PPRV-N and nectin-4 expression in PPRV-exposed goat-derived epithelial cells, which implies that PPRV replication has a role in regulating the expression of the receptor nectin-4. Conversely, the viral receptors expressed on cells may regulate viral binding, internalization, and replication [34, 35]. In the present study, we first demonstrated that PPRV uptake occurs within 1 h of exposure in goat-derived EECs and that viral replication occurs after internalization. The proliferation of PPRV in EECs observed in this study suggests that the clinical phe-nomenon of abortion in PPRV-infected goats is partly attributable to the replication of PPRV in the uterus. Furthermore, the interaction between the virus and its receptor on EECs implies that this cell line can be used to investigate the role of PPRV infection in the patho-genesis of the reproductive system in goats.
To our knowledge, this is the first broad analysis of the initial transcriptional responses to PPRV in caprine endometrial epithelial cells [11, 18, 33]. To ensure the accurate identification of the cellular genes that respond significantly to virion exposure, the DNA microarray data were scrutinized and stringently filtered with sta-tistical techniques. The expression levels of the selected genes were also experimentally verified with real-time qPCR. Using these methods for statistical verification and experimental confirmation, our study identified a large number of genes not previously implicated in the early cellular responses to PPRV infection. The detected changes in gene expression occurred within the first hours after caprine EECs were exposed to PPR viri-ons in vitro. The upregulation of pathways related to cytokine/chemokine signaling events suggests that spe-cific innate immune responses are mounted during that acute phase of PPRV insult. With a multiple-pathway ORA, we identified broad cellular functional networks that are modulated during the early course of PPRV infection, and importantly, correlated these with specific cell signaling pathways. The identities of the individual signaling pathways modulated by PPRV infection provide critical information regarding disease pathogenesis and information required for the development of novel anti-viral therapeutics.
PPRV infection in goats induces a classic inflamma-tory response, characterized by the enhanced expres-sion of cytokines such as IFN-β, IFN-γ, IL-4, IL-1β, IL-8, IL-10, IL-6, and IL-12 [18, 19]. Consistent with this, our
Figure 4 Expression patterns of all differentially expressed genes analyzed as model profiles. The expression patterns of the
study detected inflammatory factors induced by early PPRV infection. This not only confirms the accuracy of the microarray expression analysis, but also suggests that the stimulation of inflammatory cytokines occurs in the early stages of PPRV infection, during its binding and entry into caprine epithelial cells. The innate immune defense is achieved by activating the NF-κB and type I IFN (IFN-α/β) responses. It has been demonstrated that PPRV antagonizes the production of type I IFN and suppresses the host cell antiviral responses by block-ing IFN signalblock-ing by interactblock-ing with STAT1/2 [36, 37]. The present study detected no changes in IFN expres-sion in EECs exposed to PPRV for either 1 or 24 h. Fur-thermore, the upregulation of TNF-α expression and the activation of a TNF-α-related signaling pathway in the PPRV-infected EECs at 1 hpi may be attributable to the activation of the NF-κB signaling pathway. It is interest-ing to note that although some genes that have already been implicated in the pathogenesis of PPRV infection in goats, such as IL1A, IL1B, and TNFA, were induced
in the EECs at 1 hpi, they were significantly downregu-lated at 24 hpi in this study. These results contradict observations made in vivo, which indicated that the cytokine expression is upregulated for extended peri-ods of time [18, 19, 38, 39]. It is plausible that the early cytokine peak observed after high-MOI infection in vitro is only achieved at a later time during infection in vivo. Another possible explanation for this discrepancy is the difference in the duration of stimulation and therefore, the duration of the response. For instance, in vivo, prog-eny virions are continuously produced by PPRV-infected cells and will therefore bind to and enter additional tar-get cells, resulting in continuous stimulation, which may maintain cytokine production and facilitate prolonged activation [19]. Therefore, our in vitro approach probably yielded results that are indicative of the phenomenon that occurs continuously in vivo. Interestingly, the TNF (FOS, JUNB, MAP2K1, NFκBIα, SELE, and TNF), NF-κB (NFκBIα, PLAU, and TNF), and PI3K–AKT (HSP90AA1, MAP2K1, MCL1, MYC, RAC1, and VEGFA) signaling
Figure 5 Gene expression of profile Nos 2, 7, 8, and 13 during significant PPRV infection. Profiles No. 2 and No. 7 contained 222 genes
pathways were suppressed at 24 hpi. Previous studies have shown that the MV V protein binds to p65 (RELA) to suppress NF-κB activity [40]. NF-κB, receptor tyros-ine kinase, and phosphatidylinositol 3-kinase (PI3K) are important signaling pathways required for efficient viral propagation and have attracted attention as suitable tar-gets for antiviral interventions [41–44]. Previous micro-array analyses have indicated that during the infection and replication of various viruses, the genes induced in the antiviral responses include those that are involved in the activation of NF-κB [45, 46] and IRF-3 [47, 48]. Over-all, NF-κB plays an essential role in PPRV replication.
The cellular genes whose expression levels were altered after exposure to PPR virions belonged to different func-tional categories (Table 5), and encoded proteins such as inflammatory cytokines, molecules that regulate B-cell receptor signaling, chemokines, pattern recognition receptors, and proteins involved in steroid-related regu-lation, cell-cycle arrest, and cell adhesion. Our pathway ORA also identified similar functional categories of dif-ferentially regulated signaling pathways after PPRV infection. The opposite directions of the changes in immune-related gene expression in response to the bind-ing/entry (1 hpi) and replication (24 hpi) of PPRV raise
Figure 6 Gene coexpression network in EECs infected with PPRV. Genes from profile Nos 2, 7, 8, and 13 were analyzed and identified with a
Table 5 Pathways statistically significantly enriched by PPRV infection in EECs
Pathway ID Definition Fisher‑P value Enrichment_score Genes
Pathway of upregulated genes in PPRV 1 hpi
chx05140 Leishmaniasis—Capra hircus (goat) 4.22314E−06 5.374365 IL1A//NFKBIA//TGFB3//TNF chx04668 TNF signaling pathway—Capra hircus
(goat) 1.77336E−05 4.751203 CXCL1//JUNB//NFKBIA//TNF chx04380 Osteoclast differentiation—Capra
hircus (goat) 3.09217E−05 4.509736 IL1A//JUNB//NFKBIA//TNF chx05160 Hepatitis C—Capra hircus (goat) 4.21687E−05 4.37501 CLDN7//IRF1//NFKBIA//TNF chx05321 Inflammatory bowel disease (IBD)—
Capra hircus (goat) 0.000139054 3.856817 IL1A//TGFB3//TNF chx05134 Legionellosis—Capra hircus (goat) 0.000195553 3.708736 CXCL1//NFKBIA//TNF chx05133 Pertussis—Capra hircus (goat) 0.000203515 3.691403 IL1A//IRF1//TNF chx04210 Apoptosis—Capra hircus (goat) 0.000337929 3.471175 IL1A//NFKBIA//TNF chx05323 Rheumatoid arthritis—Capra hircus
(goat) 0.000409628 3.387611 IL1A//TGFB3//TNF
chx05166 HTLV-I infection—Capra hircus (goat) 0.000632975 3.198613 NFKBIA//TGFB3//TNF//ZFP36 Pathway of downregulated genes in PPRV 1 hpi
There is no enriched pathway
Pathway of upregulated genes in PPRV 24 hpi
chx05140 Leishmaniasis—Capra hircus (goat) 0.000419393 3.377379 C3//IL10//NCF1//TLR4 chx05322 Systemic lupus erythematosus—
Capra hircus (goat) 0.002795802 2.553494 C3//CD28//IL10//TROVE2 chx05205 Proteoglycans in cancer—Capra
hircus (goat) 0.002919602 2.534676 ARHGEF1//ESR1//IGF2//MMP2//TLR4 chx05320 Autoimmune thyroid disease—Capra
hircus (goat) 0.002956794 2.529179 CD28//IL10//TSHB
chx04110 Cell cycle—Capra hircus (goat) 0.003229311 2.49089 BUB1//CCNA2//CCNB1//PCNA chx05133 Pertussis—Capra hircus (goat) 0.005551826 2.255564 C3//IL10//TLR4
chx04914 Progesterone-mediated oocyte
matu-ration—Capra hircus (goat) 0.008113843 2.090773 BUB1//CCNA2//CCNB1 chx04145 Phagosome—Capra hircus (goat) 0.008982425 2.046606 C3//COLEC12//NCF1//TLR4 chx05310 Asthma—Capra hircus (goat) 0.009715281 2.012545 IL10//MS4A2
chx05323 Rheumatoid arthritis—Capra hircus
(goat) 0.01065279 1.972537 ANGPT1//CD28//TLR4 Pathway of downregulated genes in PPRV 24 hpi
chx05205 Proteoglycans in cancer—Capra
hircus (goat) 1.05326E−06 5.977465 IQGAP1//MAP2K1//MYC//PLAU//PLAUR// RAC1//SDC4//TNF//VEGFA chx04380 Osteoclast differentiation—Capra
hircus (goat) 3.21792E−06 5.492424 FOS//IL1A//JUNB//MAP2K1//NFKBIA//RAC1//TNF chx04668 TNF signaling pathway—Capra hircus
(goat) 1.89215E−05 4.723044 FOS//JUNB//MAP2K1//NFKBIA//SELE//TNF chx05020 Prion diseases—Capra hircus (goat) 2.63214E−05 4.57969 EGR1//HSPA5//IL1A//MAP2K1 chx04662 B cell receptor signaling pathway—
Capra hircus (goat) 3.0485E−05 4.515913 FOS//MAP2K1//NFKBIA//NFKBIB//RAC1 chx05140 Leishmaniasis—Capra hircus (goat) 4.28445E−05 4.368105 FOS//IL1A//NFKBIA//NFKBIB//TNF chx05323 Rheumatoid arthritis—Capra hircus
(goat) 0.000141883 3.848068 ATP6V1B2//FOS//IL1A//TNF//VEGFA chx04621 NOD-like receptor signaling
path-way—Capra hircus (goat) 0.000161774 3.791092 HSP90AA1//NFKBIA//NFKBIB//TNF chx04660 T cell receptor signaling pathway—
Capra hircus (goat) 0.000207727 3.682506 FOS//MAP2K1//NFKBIA//NFKBIB//TNF chx04620 Toll-like receptor signaling pathway—
the questions: is viral replication involved in PPRV infec-tion and what is its role in the suppression of the host immune system, especially its innate immunity? In the genus Paramyxovirus, nonstructural proteins V and C both play important roles in inhibiting the cellular anti-viral state [37, 49–51]. Recent studies have demonstrated that the PPRV V protein influences IFN signal transduc-tion by interacting with STAT1/2 [36]. Although we did not determine the expression levels of the PPRV V and C proteins, the replication of PPRV is critical for its inhi-bition of the innate-immune-related responses in goat epithelial cells. Recently, an analysis of RNA-sequencing data, followed by a functional analysis, identified the key
dysregulated genes in goat PBMCs infected with the PPR vaccine virus for 120 h, which were involved in immune-system-regulating pathways, spliceosomal pathways, and apoptotic pathways [52]. Further studies are required to establish whether there are fundamentally different cellu-lar responses to PPRV binding and entry in goat PBMCs.
Our gene coexpression network represents the most significantly expressed genes profiles at 1 and 24 hpi, with correlation coefficients of >0.9. The expression of genes involved in inflammatory activity (such as IL10,
APP, IL1A, and TLR4), immune regulation (NFKBIB, HSP90AA1, SMAD7, and JUNB), autophagy activity
(EIF2AK3), and cell-cycle progression (RAC1, ZFP36, and
Figure 7 Significant pathways associated with genes differentially expressed in EECs in response to PPRV exposure. A Upregulated
host signaling pathway modulation identified with pathway ORA in a direct comparison of mock-infected and PPRV-infected EECs at 1 h post infec-tion. B Downregulated signaling pathway modulation identified with pathway ORA in a comparison of PPRV-infected EECs at 24 and 1 h. “Enrich-ment score” indicates the enrich“Enrich-ment score value of the pathway ID, and is equal to − log10 (P value).
Figure 8 Comparison of DNA microarray and real-time PCR data. DNA microarray results and qRT–PCR quantification of the changes in
ZO3) correlated closely in goat-derived EECs in response
to PPR virion exposure. Eukaryotic translation initiation factor 2-alpha kinase 3 is an enzyme encoded in humans by the EIF2AK3 gene [53, 54]. The protein encoded by this gene phosphorylates the alpha subunit of eukaryotic translation-initiation factor 2 (EIF2), leading to its inacti-vation, and thus to a rapid reduction in the translational initiation and repression of global protein synthesis. With our gene coexpression network analysis, we identified the central role of EIF2AK3 within the PPRV-infected gene network. TLR4 plays a critical role in bacterial infec-tions by recognizing lipopolysaccharide. However, there is accumulating evidence that TLR4 is also involved in viral infections and contributes to the immune escape of MV and other viruses [55, 56]. Importantly, there are significant changes in the cytokines of the MV signaling pathway, which upregulates the expression of cytokines such as TLR4 and downregulates cytokines such as IL1α, NFκBIα, and NFκBIβ. Our study is the first to suggest that PPRV replication is closely associated with TLR4. The changes in TNF, IL1A, NFKB1A, and NFKB1B expression also indicate that the RIG1 signaling path-way and apoptosis are regulated by PPRV. HSP90AA1 was also identified as a core gene in our gene coexpres-sion analysis. HSP90AA1, a pathogen receptor, induces autophagy via an AKT–MTOR-dependent pathway dur-ing early infection [57]. MV infection regulates HSP90 expression and is closely related to the immune response [58]. Further studies should determine the role of HSP90 in regulating the intracellular signaling pathways after PPRV infection. Interestingly, our analysis identified APP, a gene involved in proinflammatory activity, as playing a central role in the gene network of PPRV-infected EECs. It is important to remember that in a previous study that characterized the response of goat-derived PBMCs to PPRV infection, APP expression was downregulated in cells after exposure to the virus for 120 h [52]. However, in the present study, APP was downregulated at 1 hpi but upregulated at 24 hpi. This prompts the fundamentally interesting question of whether PPRV induces different cellular responses in a cell-type specific or incubation-time-dependent manner.
In conclusion, our data indicate that the immediate responses of early cellular PPRV targets in EECs to virion binding and entry do not require viral gene expression. The expression of some cellular genes, such as TNF,
IL1A, and NFKB1A, was elevated in PPRV-infected EECs
at 1 hpi, but downregulated at 24 hpi, which indicates that the downregulation of these genes must be regulated by factors other than viral binding or entry. In this con-text, it is important to note that PPRV infection regulates the TNF, NF-κB, and TLR signaling pathways in EECs to resist the cellular antiviral response.
Abbreviations
PPRV: peste des petits ruminants virus; EECs: caprine endometrial epithelial cells; qRT-PCR: quantitative real-time PCR; ORA: over-representation analysis.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
BY performed the majority of experiments. ZC, SC, QX, PJ, TW participated part of the experiments. JW and XQ conceived the study, participate in its design and coordination. XQ prepared and revised the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by grants from the National Science Foundation of China (Grant No. 31602035). We are grateful to Yaping Jin (Northwest A & F University Yangling, Shaanxi, China) for the caprine endometrial epithelial cells. We thank Chinese Academy of Agricultural Sciences (Lanzhou, China) and China Animal Health and Epidemiology Center (Qingdao, China) for virus and antibody in these studies. We thank Janine Miller, Ph. D, from Liwen Bianji, Edanz Editing China, for editing the English text of a draft of this manuscript.
Ethics approval and consent to participate
Not applicable.
Author details
1 College of Veterinary Medicine, Northwest A&F University, Yangling 712100,
Shaanxi, China. 2 China Institute of Veterinary Drug Control, Beijing 100000,
China.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in pub-lished maps and institutional affiliations.
Received: 24 May 2017 Accepted: 18 December 2017
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Additional files
Additional file 1. RNA quantification and quality assurance
deter-mined spectrophotometrically with a NanoDrop ND-1000 spectro-photometer. For spectrophotometer, the O.D. A260/A280 ratio should
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Additional file 4. All genes differentially expressed in
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